code: def is_dynamic_dtype_set(op):
      # Detect if the OpInfo entry acquired dtypes dynamically
      # using `get_supported_dtypes`.
      return op.dynamic_dtypes
  
file_path: pytorch/torch/testing/_internal/opinfo/utils.py
imports: import collections
  import warnings
  from functools import partial, wraps
  from typing import Sequence
  import numpy
  import torch
  from torch.testing._internal.common_cuda import TEST_CUDA
  from torch.testing._internal.common_dtype import _dispatch_dtypes, all_types, all_types_and, all_types_and_complex, all_types_and_complex_and, all_types_and_half, complex_types, floating_and_complex_types, floating_and_complex_types_and, floating_types, floating_types_and, floating_types_and_half, integral_types, integral_types_and
  from torch.testing._internal.common_utils import torch_to_numpy_dtype_dict
label_desc: Use image node_id 3 for calling a global function with example usage: is_dynamic_dtype_set(op) and returns: op